{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jermwatt/machine_learning_refined/blob/main/notes/3_First_order_methods/A_2_Momentum.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5m8PJfs5Vu_a"
   },
   "source": [
    "## Appendix A. Advanced First- and Second-Order Optimization Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains interactive content from an early draft of the university textbook <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main\">\n",
    "Machine Learning Refined (2nd edition) </a>.\n",
    "\n",
    "The final draft significantly expands on this content and is available for <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main/chapter_pdfs\"> download as a PDF here</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YX-KWmfdVu_d"
   },
   "source": [
    "# A.2 Momentum-Accelerated Gradient Descent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "op48wlmCVu_d"
   },
   "source": [
    "In the previous Section we discussed a fundamental issue associated with the *direction* of the negative gradient: it can - depending on the function being minimized - oscillate rapidly, leading to zig-zagging gradient descent steps that slow down minimization.  In this Section we describe a popular enhancement to the standard gradient descent step, called *momentum accelerated gradient descent*, that is specifically designed to ameliorate this issue.  The core of this idea comes from the field of *time series analysis*, and in particular is a tool for smoothing time series known as the *exponential average*.  Here we first introduce the exponential average and then detail how it can be integrated into the standard gradient descent step in order to help ameliorate some of this zig-zagging (when it occurs) and consequently speeding up gradient descent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "H8PpjKOiVu_e",
    "outputId": "63932d55-e10d-4578-9510-312d27ba9135"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: github-clone in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (1.2.0)\n",
      "Requirement already satisfied: requests>=2.20.0 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (2.32.3)\n",
      "Requirement already satisfied: docopt>=0.6.2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (0.6.2)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.4.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2.2.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2024.12.14)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Cloning into 'chapter_3_datasets'...\n",
      "done.\n",
      "chapter_3_library already cloned!\n",
      "chapter_3_videos already cloned!\n"
     ]
    }
   ],
   "source": [
    "# install github clone - allows for easy cloning of subdirectories\n",
    "!pip install github-clone\n",
    "from pathlib import Path \n",
    "\n",
    "# clone datasets\n",
    "if not Path('chapter_3_datasets').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/3_First_order_methods/chapter_3_datasets\n",
    "else:\n",
    "    print('chapter_3_datasets already cloned!')\n",
    "\n",
    "# clone library subdirectory\n",
    "if not Path('chapter_3_library').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/3_First_order_methods/chapter_3_library\n",
    "else:\n",
    "    print('chapter_3_library already cloned!')\n",
    "\n",
    "# clone videos\n",
    "if not Path('chapter_3_videos').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/3_First_order_methods/chapter_3_videos\n",
    "else:\n",
    "    print('chapter_3_videos already cloned!')\n",
    "\n",
    "# append path for local library, data, and image import\n",
    "import sys\n",
    "sys.path.append('./chapter_3_library')\n",
    "sys.path.append('./chapter_3_datasets') \n",
    "sys.path.append('./chapter_3_videos') \n",
    "\n",
    "\n",
    "# import section helper\n",
    "import section_3_8_helpers\n",
    "static_plotter = section_3_8_helpers.static_visualizer()\n",
    "demo_1 = section_3_8_helpers.exponential_visualizer()\n",
    "demo_2 = section_3_8_helpers.exponential_visualizer()\n",
    "\n",
    "# data paths\n",
    "data_path_1 = 'chapter_3_datasets/ford_data.csv'\n",
    "\n",
    "# video paths\n",
    "video_path_1 = 'chapter_3_videos/animation_9.mp4'\n",
    "video_path_2 = 'chapter_3_videos/animation_10.mp4'\n",
    "\n",
    "# standard imports\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from IPython.display import Image, HTML\n",
    "from base64 import b64encode\n",
    "\n",
    "def show_video(video_path, width = 1000):\n",
    "    video_file = open(video_path, \"r+b\").read()\n",
    "    video_url = f\"data:video/mp4;base64,{b64encode(video_file).decode()}\"\n",
    "    return HTML(f\"\"\"<video width={width} controls><source src=\"{video_url}\"></video>\"\"\")\n",
    "\n",
    "\n",
    "# import autograd-wrapped numpy\n",
    "import autograd.numpy as np\n",
    "from autograd import value_and_grad \n",
    "\n",
    "# this is needed to compensate for matplotlib notebook's tendancy to blow up images when plotted inline\n",
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.autolayout'] = True\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "H7871y7yVu_g"
   },
   "source": [
    "##  The exponential average"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1QQAI18dVu_h"
   },
   "source": [
    "In the figure below we show an example of a *time series* dataset.  This particular example comes from a real snippet of a financial time series - a history of the price of a financial stock over 500 periods of time.  However time series datasets abound in science, engineering, and buisness (and are a subject of particular study in machine learning, as we discuss in a future Chapter).  More specifically, a time series dataset consists of a sequence of $K$ *ordered points* $w^1,\\,w^2,\\,...,w^K$.  Note: These points are assumed *ordered*, meaning that the point $w^1$ comes before (that is, it is created and / or collected before) $w^2$, the point $w^2$ before $w^3$, and so on.   For example we *generate* a time series of points whenever we run a local optimization scheme with steps\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^k = \\mathbf{w}^{k-1} + \\alpha \\mathbf{d}^{k-1}\n",
    "\\end{equation}\n",
    "\n",
    "\n",
    "which produces the time series sequence of ordered points $\\mathbf{w}^{1},\\,\\mathbf{w}^{2},\\,...,\\mathbf{w}^{K}$ that are potentially multi-dimensional."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5kI13t6WVu_h"
   },
   "source": [
    "In any case, because the raw values of a time series often oscillates or *zig-zags* up and down it is common practice to *smooth them* to remove these zig-zagging motions prior to further analysis.  The *exponential average* is one of the most popular such smoothing techniques for time series, and is used in virtually every application in which time series arise.  We show the result of smoothing the example time series below via the exponential average - with the resulting exponential average shown as a orange curve.  Note that the first average point - set to be the first point of the input series $x_1$ - is shown as a pink dot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "id": "chWbL6e8Vu_i",
    "outputId": "cf095079-2e41-4788-b3b7-7b534139e626"
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 900x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load in data\n",
    "data = pd.read_csv(data_path_1)\n",
    "x = np.array(data['Close'])    # date: 1980 to 2017\n",
    "\n",
    "# exponential average function\n",
    "def exponential_average(x,alpha):\n",
    "    h = [x[0]]\n",
    "    for p in range(len(x) - 1):\n",
    "        # get next element of input series\n",
    "        x_p = x[p]\n",
    "        \n",
    "        # make next hidden state\n",
    "        h_p = alpha*h[-1] + (1 - alpha)*x_p\n",
    "        h.append(h_p)\n",
    "    return np.array(h)\n",
    "\n",
    "# produce moving average time series\n",
    "alpha = 0.9\n",
    "h = exponential_average(x,alpha)\n",
    "\n",
    "# run animator\n",
    "demo_1.animate_exponential_ave(x,h,savepath=video_path_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 376
    },
    "id": "adlvOJ3YV4sl",
    "outputId": "3cdd02f1-6df6-4c30-af7d-389f229f5efd"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video width=800 controls><source 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_video(video_path_1, width=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ybrfc3CsVu_k"
   },
   "source": [
    "Below we animate the same running average process as shown above for the same input series - but for only the first 50 points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "id": "6DcPjqFzVu_k",
    "outputId": "fa07694f-d261-42a5-e397-418369031fa7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# run animator\n",
    "demo_2.animate_exponential_ave(x[:100],h[:100],savepath=video_path_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 376
    },
    "id": "QB0S7PlXWi9s",
    "outputId": "43ae16c1-b053-4a2b-822c-9dbe658dec0e"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video width=800 controls><source 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_video(video_path_2, width=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YgzWQrZOVu_l"
   },
   "source": [
    "Before we see how the exponential average is computed lets first see how to compute a *running average* of $K$ input points $w^1,\\,w^2,\\,...,w^K$, that is the average of the first two points, the average of the first three points, and so forth.  Naively we could write down this running average as so"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "apHELMM2Vu_l"
   },
   "source": [
    "\\begin{array}\n",
    "\\\n",
    "\\text{average of the first $1$ elements:} \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, h^1 = w^1 \\\\\n",
    "\\text{average of the first $2$ elements:} \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, h^2 = \\frac{w^1 + w^2}{2} \\\\\n",
    "\\text{average of the first $3$ elements:} \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, h^3 = \\frac{w^1 + w^2 + w^3}{3} \\\\\n",
    "\\text{average of the first $4$ elements:} \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, h^4 = \\frac{w^1 + w^2 + w^3 + w^4}{4} \\\\\n",
    "\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, \\vdots \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, \\vdots \\\\\n",
    "\\text{average of the first $k$ elements:} \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, h^{k} = \\frac{w^1 + w^2 + w^3 + w^4 + \\cdots  + w^k}{k} \\\\\n",
    "\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, \\vdots \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\, \\vdots \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Cq2y0A8FVu_l"
   },
   "source": [
    "Notice how at each step here the average computation $h^t$ *summarizes* the input points $w^1$ through $w^k$ via a simple summary statistic: their sample mean.   However as written above, we *need every raw point $w^1$ through $w^k$* in order to compute the running average $h^k$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rMnmScgQVu_m"
   },
   "source": [
    "Fortunately we can write this running average more effeciently by studying the form of each computation.  For example notice how the average of $x^1$ and $x^2$ can be written as\n",
    "\n",
    "\\begin{equation}\n",
    "h^2 = \\frac{w^1 + w^2}{2} = \\frac{h^1 + w^2}{2} = \\frac{1}{2}h^1 + \\frac{1}{2}w^2.\n",
    "\\end{equation}\n",
    "\n",
    "Likeiwse, looking at the next line we can write $h^4$ in terms of its predecessor $h^3$ as \n",
    "\n",
    "\\begin{equation}\n",
    "h^3 = \\frac{w^1 + w^2 + w^3}{3} = \\frac{2\\frac{w^1 + w^2}{2} + w^3}{3} = \\frac{2h^2 + w^3}{3} = \\frac{2}{3}h^2 + \\frac{1}{3}w^3.\n",
    "\\end{equation}\n",
    "\n",
    "In general we can express the $k^{th}$ running average $h^{k}$ for $k > 1$ in the same sort of way, involving only its preceeding running average and raw time series value as\n",
    "\n",
    "\\begin{equation}\n",
    "h^{k} = \\frac{k-1}{k}h^{t-1} + \\frac{1}{k}w^k.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h0ILSH-5Vu_m"
   },
   "source": [
    "What is the benefit of writing the *running average* in this way, as opposed to the naive way given above?  Imagine we computed the running average one update at a time from $h^1$ all the way to $h^k$.  When compared to the naive way of computing the average\n",
    "\n",
    "\\begin{equation}\n",
    "h^{k} = \\frac{w^1 + w^2 + w^3 + w^4 + \\cdots + w^k}{k}\n",
    "\\end{equation}\n",
    "\n",
    "here we need to know (i.e., store) the explicit values of every value up to and including $w^k$ (that is $w^1$ through $w^{k}$), whereas with the clever way of writing the same average above we only need to access two values: $w^k$ and $h^{k-1}$.  From a computational perspective, this is far more memory effecient (since at each step we only need to store and deal with two values as opposed to $t$ of them).  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8vWrEjs4Vu_m"
   },
   "source": [
    "The *exponential average* is a simple generalization of this running average formula.  Notice that at every step in the clever recursion in equation for the running average in (3) that the coeffecients on the two terms in the update *always sum to $1$*: that is $\\frac{k-1}{k} + \\frac{1}{k} = 1$ for all $k$ always.  At each step both coeffecients change as $\\frac{k-1}{k}$ and $\\frac{1}{k}$ respectively, and the to create the exponential average we use the same update formula but *freeze the coeffecients*.  That is, using the same initial value $h^1 = w^1$ and for $k > 1$ we take a value $\\beta \\in \\left[0,1\\right]$ and create a running *exponential average* via the similar formula\n",
    "\n",
    "\\begin{equation}\n",
    "h^{k} = \\beta \\, h^{k-1} +  \\left(1 - \\beta\\right)w^k.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TuCreaOLVu_m"
   },
   "source": [
    "Clearly the parameter $\\beta$ here controls a tradeoff: the smaller we set $\\beta$ the more our exponential average approximates the raw (zig-zagging) time series itself, while the larger we set it the more each subsequent average looks like its predecessor.  However regardless of how we set $\\beta$ each step $h^k$ in an exponential average - like the running average - summarizes *every point in the time series that preceeds it* $w^1,\\,w^2,\\,...,w^{k}$.\n",
    "\n",
    ">  Each step $h^k$ in an exponential average - like the running average - summarizes *every point in the time series that preceeds it*: $w^1,\\,w^2,\\,...,w^{k}$\n",
    "\n",
    "Why is this slightly adjusted version of the running average called an *exponential average*?  Because if we 'roll back' the update shown above back - expressing each update step $h^k$ in terms of all its preceeding elements - we can see the exponential relationship explicitly.  We show this algebraic manipulation below.  Needless to say with this update - as with the running average - *each and every step $h^k$ summarizes the elements of the input that preceeds it* ($w^1$ through $w^k$) via an (exponential) average."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5tKnR6XvVu_m"
   },
   "source": [
    "By using the exponential averaging formula above - and substituting in the value of each preceeding value $h^{k-1}$, all the way back to $h^1$ - we can 'roll back' the exponential average at each step so that $h^k$ is expressed entirely in terms of the input values $w^1$ through $w^k$ preceeding it.  For example, substituting in the same formula for $h^{k-1} = \\beta \\, h^{k-2} +  \\left(1 - \\beta\\right)w^{k-1}$ into the right hand side above for $h^k$ gives after simplifying\n",
    "\n",
    "\\begin{equation}\n",
    "h^k = \\beta \\, h^{k-1} +  \\left(1 - \\beta\\right)w^k = \\beta\\left(\\beta\\, h^{k-2} + \\left(1 - \\beta\\right)w^{k-1}\\right) + \\left(1 - \\beta\\right) w^k = \n",
    "\\left(\\beta\\right)^2 \\, h^{k-2} + \\beta  \\left(1 - \\beta\\right)w^{k-1} + \\left(1 - \\beta\\right) w^k.\n",
    "\\end{equation}\n",
    "\n",
    "Note here that the notation $\\left(\\beta\\right)^2$ means *raise the constant $\\beta$ to the second power* i.e., $\\beta = \\beta \\times \\beta$, whereas our typical superscript notation $h^{k-1}$ and $w^{k-1}$ still denotes the $\\left(k-1\\right)^{th}$ element of each of these sequences respectively."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "r4RgRxlnVu_m"
   },
   "source": [
    "If we continue doing this we can 'roll back' all the way to the initial condition - which expresses our step $h^k$ in terms of *every input sequence value $w^1$ through $w^k$* as \n",
    "\n",
    "\\begin{equation}\n",
    "h^{k} = \\left(\\beta\\right)^{\\,k} \\, w^1 + \\left(\\beta\\right)^{\\,k-1}\\,\\left(1 - \\beta\\right) w^{2} + \\left(\\beta\\right)^{\\,k-2}\\left(1 - \\beta\\right)w^3 + \\cdots  + \\beta\\,\\left(1 - \\beta\\right)w^{k-1}  + \\left(1 - \\beta\\right)w^k \n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4-tVjD5CVu_n"
   },
   "source": [
    "Aain note here that the notation $\\left(\\beta\\right)^k$ means *raise the constant $\\beta$ to the $k^{th}$ power* whereas our typical superscript notation $h^{k-1}$ and $w^{k-1}$ still denotes the $\\left(k-1\\right)^{th}$ element of each of these sequences respectively.\n",
    "\n",
    "Also note: by unwravelling the definition of $h^k$ we can indeed see that it is a function (an average) of *every point of the time series that preceeds it*: $w^1,\\,w^2,\\,...,w^{k}$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jyjlvqO7Vu_n"
   },
   "source": [
    "Of course just as with the running average we prefer our simple update step for the exponential average\n",
    "\n",
    "\\begin{equation}\n",
    "h^{k} = \\beta \\, h^{k-1} +  \\left(1 - \\beta\\right)w^k\n",
    "\\end{equation}\n",
    "\n",
    "over such a long list of formulae, as it is far more effecient (requiring only two values per update compared with $k$). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_JXRS41xVu_n"
   },
   "source": [
    "Lastly, note that in deriving the exponential average we assumed our time series was *one-dimensional*, that is each raw point $w^k$ has only a single dimension.  However this idea holds for time series *irregardless of their input dimension* (like the steps of a local optimization run).  We can likewise define the exponential average of a time series of general $N$ dimensional points $\\mathbf{w}^1,\\,\\mathbf{w}^2,\\,...,\\mathbf{w}^K$ by initializing $\\mathbf{h}^1 = \\mathbf{w}^1$ and then for $k > 1$ building $\\mathbf{h}^k$ as \n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{h}^{k} = \\beta \\, \\mathbf{h}^{k-1} +  \\left(1 - \\beta\\right)\\mathbf{w}^k.\n",
    "\\end{equation}\n",
    "\n",
    "Here the exponential average at step $k$ $\\mathbf{h}^k$ is also $N$ dimensional."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_QuLK-rrVu_n"
   },
   "source": [
    "##  Ameliorating the zig-zag behavior of gradient descent "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fxYVlyM_Vu_n"
   },
   "source": [
    "In the previous Section we saw how our gradient descent scheme\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^{\\,k} = \\mathbf{w}^{\\,k-1} - \\alpha \\nabla g\\left(\\mathbf{w}^{k-1}\\right)\n",
    "\\end{equation}\n",
    "\n",
    "naturally suffers from zig-zagging behavior that slows progress of minimization.  Notice that, in the context of our discussion above regarding the exponential average, both our sequence of gradient descent steps (or any local optimization scheme for that matter) *and* the negative gradient directions themselves are both *time series*.  Indeed if we take $K$ steps of gradient descent using the form above we do create an time series of ordered *gradient descent steps* $\\mathbf{w}^1,\\,\\mathbf{w}^{1},\\,...,\\mathbf{w}^{K}$ and descent directinos $-\\nabla g\\left(\\mathbf{w}^{0}\\right),\\,-\\nabla g\\left(\\mathbf{w}^{1}\\right),...,-\\nabla g\\left(\\mathbf{w}^{K-1}\\right)$.  In the context of local optimization we use the index $k$ instead of $t$, but besides this slight notational difference these are indeed time series."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VFcsByIsVu_n"
   },
   "source": [
    "To attempt to ameliorate some of the zig-zagging behavior of our gradient descent steps  $\\mathbf{w}^1,\\,\\mathbf{w}^{1},\\,...,\\mathbf{w}^{K}$ we could compute their *exponential average*, as this will surely smooth them out much as they did in the example used to introduce the exponential average above.  However we do not want to smooth the gradient descent steps *after* they have been created - the 'damage is already done' in the sense that the zig-zagging has already slowed the progress of a gradient descent run.  Instead what we want is to smooth the steps *as they are created*, so that our algorithm makes more progress in minimization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jlUo4OM7Vu_o"
   },
   "source": [
    "How do we smooth the steps as the are made?  Remember from the previous Section that the root cause of zig-zagging gradient descent steps zig-zag is the oscillating nature of the (negative) gradient directions themselves.  In other words, if the descent directions $-\\nabla g\\left(\\mathbf{w}^{0}\\right),\\,-\\nabla g\\left(\\mathbf{w}^{1}\\right),...,-\\nabla g\\left(\\mathbf{w}^{K-1}\\right)$ zig-zag, so to will the gradient descent steps.  So it seems reasonable to suppose that if we smooth out these directions as they are created during a run of local optimization we can - as a consequence - produce steps that do not zig-zag as much and therefore make more progress in minimization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mE_jYSW6Vu_o"
   },
   "source": [
    "Using the exponential average explained earlier in this Section, we will to create our smoothed descent directions as they are created.  We initialize $\\mathbf{d}^0 = \\nabla g\\left(\\mathbf{w}^0\\right)$ and then for $k -1 > 0$ the $\\left(k-1\\right)^{th}$ exponentially averaged descent direction $\\mathbf{d}^{k-1}$ takes the form (by the very definition of the exponentially average given previously) \n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{d}^{k-1} = \\beta \\, \\mathbf{d}^{k-2} -  \\left(1 - \\beta\\right)\\nabla g\\left(\\mathbf{w}^{k-1}\\right)\n",
    "\\end{equation}\n",
    "\n",
    "\n",
    "We can then use this descent direction in our generic local optimization framework to step as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^{\\,k} = \\mathbf{w}^{\\,k-1} + \\alpha \\, \\mathbf{d}^{k-1}.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_tkpw8ofVu_o"
   },
   "source": [
    "Together this exponential averaging adds only a single step to our gradient descent scheme - which together are\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{d}^{k-1} = \\beta \\, \\mathbf{d}^{k-2}  - \\left(1 - \\beta\\right)\\nabla g\\left(\\mathbf{w}^{k-1}\\right) \\\\\n",
    "\\mathbf{w}^{\\,k} = \\mathbf{w}^{\\,k-1} + \\alpha \\, \\mathbf{d}^{k-1}. \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,      \\,\\,\\,\n",
    "\\end{equation}\n",
    "\n",
    "Nonetheless since this simple adjustment was explicitly designed to help ameliorate the zig-zagging problem that can occur with standard gradient descent it can be substantially more effective.  This simple adjustment to gradient descent is often called *momentum acclerated gradient descent*.  The term 'momentum' here refers to the new exponentially averaged descent direction $\\mathbf{d}^{k-1}$.  Notice that by the very definition of the exponential gradient given in the first part of this Section, that this descent direction $\\mathbf{d}^{k-1}$ is a function (an exponential average) of *every negative gradient which preceeds it* $-\\nabla g\\left(\\mathbf{w}^{0}\\right),\\,-\\nabla g\\left(\\mathbf{w}^{1}\\right),...,-\\nabla g\\left(\\mathbf{w}^{k-1}\\right)$\n",
    "\n",
    "> The descent direction used in accelerated gradient descent is an exponential average, meaning that $\\mathbf{d}^{k-1}$ is an exponential average of every negative gradient direction preceeding it $-\\nabla g\\left(\\mathbf{w}^{0}\\right),\\,-\\nabla g\\left(\\mathbf{w}^{1}\\right),...,-\\nabla g\\left(\\mathbf{w}^{k-1}\\right)$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "i9L6sf0wVu_o"
   },
   "source": [
    "As with any exponential average the choice of $\\beta \\in \\left[0,1\\right]$ provides a trade-off between here.  The smaller $\\beta$ is chosen the *more* the exponential average resembles the actual sequence of negative descent directions since *more* of each negative gradient direction is used in the update, but the *less* these descent directions summarize all of the previously seen negative gradients.  The larger $\\beta$ is chosen the *less* these exponentially averaged descent steps resemble the negative gradient directions, since each update will use *less* of each subsequent negative gradient direction, but the *more* they represent a summary of them.  Often in practice larger values of $\\beta$ are used, in the range $\\left[0.7,1\\right]$, meaning that often in practice a strongly summarizing descent direction $\\mathbf{d}^{k-1}$ tends to provide better performance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h5ZFR4jwVu_o"
   },
   "source": [
    "Note in practice this step is also written slightly differently than above, although this notational re-arrangement ammounts to exactly the same thing: instead of averaging the *negative* gradient directions the gradient itself is exponentially averaged, and then the *step* is taken in their *negative* direction.  This means that we initialize our exponential average at the first *negative* descent direction $\\mathbf{d}^0 = -\\nabla g\\left(\\mathbf{w}^0\\right)$ and for $k-1 > 0$ the general descent direction and corresponding step is computed as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{d}^{k-1} = \\beta \\, \\mathbf{d}^{k-2} +  \\left(1 - \\beta\\right)\\nabla g\\left(\\mathbf{w}^{k-1}\\right) \\\\\n",
    "\\mathbf{w}^{\\,k} = \\mathbf{w}^{\\,k-1} - \\alpha \\, \\mathbf{d}^{k-1}. \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,      \\,\\,\\,\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dMxI1WtdVu_o"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 1. </span>  Gradient descent directions on the contour plot of a quadratic function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "djS3kiIkVu_o"
   },
   "source": [
    "In this example we compare a run of standard gradient descent to the *momentum accelerated* version detailed above using the first quadratic from Example 4 of the previous Section.  This pure quadratic has zero constant and linear terms and a matrix $\\mathbf{C} = \\begin{bmatrix} 0.5\\,\\,0 \\\\ 0 \\,\\, 12\\end{bmatrix}$, and has a global minimum at the origin $\\mathbf{w}=\\begin{bmatrix} 0 \\\\ 0 \\end{bmatrix}$.  Here we re-produce the same run of $25$ gradient descent steps shown in this prior example, and also compare two run of *momentum accelerated graient descent* with two choices for $\\beta \\in \\{0.2, 0.7\\}$.  All three runs are initialized at the same point $\\mathbf{w}^0 = \\begin{bmatrix} 10 \\\\ 1 \\end{bmatrix}$ and use the same learning rate $\\alpha = 10^{-1}$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iBDu6tR2Vu_o"
   },
   "source": [
    "We show the resulting steps taken by the standard gradient descent run in the top panel (where significant zig-zagging is present), and the momentum accelerated versions using $\\beta = 0.2$ and $\\beta = 0.7$ in the middle and bottom panels respectively.   Both momentum accelerated versions outperform the standard scheme, in that they reach a point closer to the true minimum of the quadratic, and clearly zig-zagging is significantly reduced in both momentum accelerated runs.   The choice of $\\beta = 0.7$ provides better performance because it reduces zig-zagging while maintaining larger steplength - since its stronger summarizing descent direction maintains a larger magnitude (from the first steps of the run which are far from the minimum where the magnitude of the negative gradient was large) as the run approaches the minimum of the quadratic.  The case where $\\beta = 0.2$, which is closer to the original negative gradient, starts taking smaller steps as it approaches the minimum since its descent direction more closely resembles the true negative gradient (whose magnitude is diminishing rapidly)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "z5vuw-SOVu_p"
   },
   "outputs": [],
   "source": [
    "# using an automatic differentiator - like the one imported via the statement below - makes coding up gradient descent a breeze\n",
    "# gradient descent function - inputs: g (input function), alpha (steplength parameter), max_its (maximum number of iterations), w (initialization)\n",
    "def momentum(g,alpha_choice,beta,max_its,w):\n",
    "    # compute the gradient function of our input function - note this is a function too\n",
    "    # that - when evaluated - returns both the gradient and function evaluations (remember\n",
    "    # as discussed in Chapter 3 we always ge the function evaluation 'for free' when we use\n",
    "    # an Automatic Differntiator to evaluate the gradient)\n",
    "    gradient = value_and_grad(g)\n",
    "\n",
    "    # run the gradient descent loop\n",
    "    weight_history = []      # container for weight history\n",
    "    cost_history = []        # container for corresponding cost function history\n",
    "    alpha = 0\n",
    "    cost_eval,grad_eval = gradient(w)\n",
    "    \n",
    "    # initialization for momentum direction\n",
    "    h = np.zeros((w.shape))\n",
    "    for k in range(1,max_its+1):\n",
    "        # check if diminishing steplength rule used\n",
    "        if alpha_choice == 'diminishing':\n",
    "            alpha = 1/float(k)\n",
    "        else:\n",
    "            alpha = alpha_choice\n",
    "        \n",
    "        # evaluate the gradient, store current weights and cost function value\n",
    "        cost_eval,grad_eval = gradient(w)\n",
    "        weight_history.append(w)\n",
    "        cost_history.append(cost_eval)\n",
    "        \n",
    "        #### momentum step - update exponential average of gradient directions to ameliorate zig-zagging ###\n",
    "        h = beta*h - (1 - beta)*grad_eval\n",
    "\n",
    "        # take gradient descent step\n",
    "        w = w + alpha*h\n",
    "            \n",
    "    # collect final weights\n",
    "    weight_history.append(w)\n",
    "    # compute final cost function value via g itself (since we aren't computing \n",
    "    # the gradient at the final step we don't get the final cost function value \n",
    "    # via the Automatic Differentiatoor) \n",
    "    cost_history.append(g(w))  \n",
    "    return weight_history,cost_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 509
    },
    "id": "_J8TFFQCVu_p",
    "outputId": "0b96f62e-7490-4914-c847-8bc2b1f6d70c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define constants for a N=2 input quadratic\n",
    "a1 = 0\n",
    "b1 = 0*np.ones((2,1))\n",
    "C1 = np.array([[0.5,0],[0,9.75]])\n",
    "\n",
    "# a quadratic function defined using the constants above\n",
    "g = lambda w: (a1 + np.dot(b1.T,w) + np.dot(np.dot(w.T,C1),w))[0]\n",
    "\n",
    "w = np.array([10.0,1.0]); max_its = 25; alpha_choice = 10**(-1);\n",
    "beta = 0\n",
    "weight_history_1,cost_history_1 = momentum(g,alpha_choice,beta,max_its,w)\n",
    "\n",
    "beta = 0.1;\n",
    "weight_history_2,cost_history_2 = momentum(g,alpha_choice,beta,max_its,w)\n",
    "\n",
    "beta = 0.7\n",
    "weight_history_3,cost_history_3 = momentum(g,alpha_choice,beta,max_its,w)\n",
    "\n",
    "# show run in both three-dimensions and just the input space via the contour plot\n",
    "histories = [weight_history_1,weight_history_2,weight_history_3]\n",
    "gs = [g,g,g]\n",
    "static_plotter.two_input_contour_vert_plots(gs,histories,num_contours = 25,xmin = -1.5,xmax = 10.5,ymin = -2.0,ymax = 1.5)"
   ]
  }
 ],
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   "name": "python3"
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
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  "toc": {
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